A Dual-Adaptive Approach Based on Discrete Cosine Transform for Removal of ECG Baseline Wander

Removal of baseline wander (BW) is an important preprocessing step before manually or automatically interpreting electrocardiogram (ECG) records. It is a challenging issue to fully remove BW while preserving original clinical information because BW is usually mingled with low-frequency ECG components. A dual-adaptive approach based on discrete cosine transform (DCT) is presented in this study. Firstly, the cardiac fundamental frequency (CFF) of ECGs is accurately calculated through DCT domain analysis. Secondly, DCT coefficients of ECGs, whose frequencies are below CFF, are used to construct an amplitude vector in which the optimal cut-point between BW and ECGs is distinctly reflected. Finally, a new filtering technique based on DCT is exploited to suppress BW with its cutoff frequency adjusted to the optimal cut-point. The proposed method is applied to both real ECG records and simulated ECGs with its results compared to those of three previous methods published in the literature. The experimental results show that substantial improvements in performance can be achieved when adopting this dual-adaptive approach.

Automated summary

This study proposes a dual-adaptive approach based on DCT for the removal of baseline wander in ECG records. The method accurately calculates the cardiac fundamental frequency and uses DCT coefficients to distinguish between baseline wander and ECG. A new filtering technique based on DCT is then applied to suppress baseline wander. Experimental results demonstrate significant improvements in performance when using this dual-adaptive approach.